CHARACTERISATION OF PARTICULATE MATTER OF TRAFFIC ORIGIN IN SINGAPORE YANG TZUO SERN NATIONAL UNIVERSITY OF SINGAPORE 2004 CHARACTERISATION OF PARTICULATE MATTER OF TRAFFIC ORIGIN IN SINGAPORE YANG TZUO SERN (B. Eng. (Hons), RMIT) A THESIS SUBMITTED FOR THE DEGREE OF MASTER OF ENGINEERING DEPARTMENT OF CHEMICAL AND BIOMOLECULAR ENGINEERING NATIONAL UNIVERSITY OF SINGAPORE 2004 In memory of my beloved mother Acknowledgements This project would not be initiated and completed without the scholarship awarded by Department of Chemical and Biomolecular Engineering, National University of Singapore and the BALASUBRAMANIAN. guidance and supervision of Dr. Rajasekhar I wish to thank him for his opinions and the fruitful discussions that we have had throughout this research period. I also wish to extend my greatest appreciation to my team-mate cum best friend ER Show Lin for her courtesy helps and supports throughout the period of my research. Special thanks to Ellis SEE Siao Wei, Dr. Rajenara Kumar RATH and YAP Hui San for their assistance in this research. I like to extend my gratitude to LI Fengmei, Susan CHIA and LI Xiang for their helps in logistic procurement and handling as well as instrument operating in the laboratory. Their assistance and co-operation have made this project successful. I wish to extend my gratitude to Instituto de Pesquisas Energéticas e Nucleares SP, Instituto de Química of University of São Paulo, Brazil, especially Dr. Vasconcellos, for their help in analysing the samples. A special appreciation is extended to Land Transport Authority of Singapore for permitting us to conduct the sampling at the Boon Lay bus interchange. Lastly, I like to thank all my family members and friends who have been very supportive throughout the period. Characterization of PM of Traffic Origin in Singapore 2004 i Table of Contents Table of Contents Acknowledgement ........................................................................................................ i Table of Contents......................................................................................................... ii Summary ......................................................................................................................v Nomenclature ........................................................................................................... viii List of Figures...............................................................................................................x List of Tables.............................................................................................................xiv Chapter 1 1.1 Introduction ...............................................................................................1 Objectives .....................................................................................................4 Chapter 2 2.1 Literature Review ......................................................................................5 Sources of Atmospheric Particulate Matter ....................................................5 2.1.1 Natural sources ......................................................................................6 2.1.2 Anthropogenic sources...........................................................................8 2.2 Measurement of Particulate Matter ..............................................................12 2.2.1 Particle mass........................................................................................12 2.2.2 Particle number....................................................................................14 2.2.3 Particle surface area .............................................................................14 2.2.4 Particle size classification ....................................................................15 2.2.5 Particle Chemical Composition............................................................16 2.3 Particulate Matter from Diesel Source .........................................................19 2.3.1 Nanoparticles.......................................................................................22 2.3.2 Diesel exhaust particle composition and structure ................................23 2.4 Particulate Matter Health and Environmental Impacts .................................24 2.4.1 Health impacts .....................................................................................24 Characterization of PM of Traffic Origin in Singapore 2004 ii Table of Contents 2.4.2 Environmental impacts ........................................................................27 Chapter 3 Sampling Site Description .......................................................................31 3.1 NUS FoE Air Quality Monitoring Station....................................................31 3.2 Punggol Multi-storey Car Park Rooftop.......................................................32 3.3 Boon Lay Bus Interchange...........................................................................33 Chapter 4 4.1 Instruments and Analytical Procedures ....................................................36 On-site Sampling Instruments......................................................................36 4.1.1 Annular Denuder System (ADS) ..........................................................36 4.1.2 MiniVol® Portable Air Sampler ...........................................................39 4.1.3 AethalometerTM ...................................................................................39 4.1.4 Micro-Orifice Uniform Deposit Impactor (MOUDITM Model 110) ......40 4.1.5 Hi-Vol Sampler HVP-3800AFC/230....................................................41 4.1.6 Condensation Particles Counter (CPC) TSI 3007 .................................41 4.1.7 Electrical Low Pressure Impactor (ELPI) (Dekati Ltd.)........................42 4.1.8 Scanning Mobility Particle Sizer (SMPS) TSI 3034 .............................42 4.2 Analytical Instruments and Methodology.....................................................43 4.2.1 Microbalance Sartorius MC-5 ..............................................................43 4.2.2 MLS-1200 MEGA Microwave Digestion System ................................44 4.2.3 ICP-MS Perkin Elmer Elan 6100 .........................................................45 4.2.4 Ion Chromatography – Metrohm Ion Analyzer.....................................45 4.2.5 Soxhlet Apparatus................................................................................47 Chapter 5 Results and Discussion ............................................................................48 5.1 Mass Concentration .....................................................................................48 5.1.1 Background .........................................................................................48 5.1.2 Measurement of PM2.5 mass concentration...........................................50 Characterization of PM of Traffic Origin in Singapore 2004 iii Table of Contents 5.1.3 PM Mass Size Distribution ..................................................................53 5.1.4 Black Carbon Mass Concentration .......................................................58 5.2 Number Concentration ................................................................................60 5.2.1 Background .........................................................................................60 5.2.2 Total Particle Number Concentration ...................................................63 5.2.3 PM Number Size Distribution..............................................................66 5.3 Chemical Characterization...........................................................................70 5.3.1 Background .........................................................................................70 5.3.2 Chemical Composition of PM2.5 ...........................................................71 5.3.3 Mass Size Distribution of Ions and Trace Elements..............................93 Chapter 6 Conclusions ...........................................................................................106 Appendix A ..............................................................................................................110 Appendix B...............................................................................................................111 Appendix C...............................................................................................................112 References ................................................................................................................118 Characterization of PM of Traffic Origin in Singapore 2004 iv Summary Summary Among the major sources of air pollution in urban areas, emissions from on-road vehicles are of particular concern since they occur in close proximity to human beings. Particulate matter is one of the major pollutants derived from vehicular emissions, and has potential adverse effects on human health and the environment. The particulate matter (PM) in the urban atmosphere is mainly derived from the incomplete combustion of carbonaceous fuels, especially diesel. Airborne particulate matter is a highly complex entity. It is a perfect carrier of nonairborne toxic and carcinogenic materials such as polyaromatic hydrocarbons (PAHs). In order to assess the health risk associated with particulate air pollution, an extensive field study was conducted to gather the information about the mass and number concentration of particulate matter, their respective size distributions and their chemical composition at three different locations in Singapore. These locations include the rooftop of a multi-storey car park at a residential area near an expressway, the rooftop of one of the tall buildings at the National University of Singapore campus, and a busy bus interchange with a majority of diesel-driven buses. Gravimetric air samplers and sophisticated particulate analysers were deployed at strategic locations to collect PM samples and to measure particulate counts. MiniVol® and Hi-Vol air samplers were used to collect PM2.5 (particle size smaller than 2.5µm in diameter) and Total Suspended Particles (TSP) samples, respectively. A Micro-orifice Characterization of PM of Traffic Origin in Singapore 2004 v Summary Uniform Deposit Impactor (MOUDITM) was used to study PM mass size distribution at each of the sampling sites. AethalometerTM was deployed to measure real time black carbon (BC) diurnal emission profile. A portable Condensation Particles Counter (CPC) was used to count the total number of particles with diameters greater than 10 nm while Electrical Low Pressure Impactor (ELPI) and Scanning Mobility Particle Sizer (SMPS) measured real time particulate number size distribution. Weather conditions and surrounding human activities were closely monitored. The aerosol samples collected from the sites were carefully sealed and returned to the laboratory for the analysis of selected chemical components including water-soluble ionic species, microwave extractable trace elements and a range of organic compounds by gas chromatography. The relationship among particle mass, number and size distribution was investigated. This study revealed that the PM concentration at the bus interchange was approximately 3 times the mass but over 10 times the number concentration measured at the university campus, which is considered to be an urban background location in this study. This suggests that the level of potential occupational health risk that an individual is exposed to in the bus interchange is probably higher than that in other urban microenvironments due to inhalation of ultrafine particles in large numbers. Black carbon accounted for 50% of the total PM2.5 mass loading at the bus interchange, but was only 17% of that measured in the urban background location. A positive correlation between BC and particle number concentration strongly suggested that traffic emission is possibly the most important source of ultrafine particles in the urban air of Singapore. Water-soluble sulphate concentration measured at the bus interchange was not significantly different from the background concentration, indicating that Characterization of PM of Traffic Origin in Singapore 2004 vi Summary sulphuric acid formation was rather slow hence lower sulphate condensation taking place onto the particle. Concentration of particle-bound PAHs, Zn, Cu, Fe and Ti appeared to be much higher than that measured at the background location. The CPI, carbon preference index of n-alkane fractions identified fossil fuel combustion as the main source of n-alkanes at the bus interchange. Toxic Equivalent Factor evaluation suggested that B(a)P was one of the main carcinogens among the whole cluster of measured PAHs. Characterization of PM of Traffic Origin in Singapore 2004 vii Nomenclature Nomenclature Abbreviations AYE Ayer Rajah Expressway BC Black carbon BKE Bukit Timah Expressway CCN Cloud Condensation Nuclei CPI Carbon Preference Index CTE Central Expressway DMS Dimethylsulphide EC Elementary carbon ECP East Coast Expressway ELPI Electrical Low Pressure Impactor FoE Faculty of Engineering HDB Housing Development Board KJE Kranji Expressway NUS National University of Singapore PIE Pan-Island Expressway PM Particulate Matter PM10 Particulate matter smaller than 10 µm in aerodynamic diameter PM2.5 Particulate matter smaller than 2.5 µm in aerodynamic diameter SLE Seletar Expressway SMPS Scanning Mobility Particle Sizer SOA Secondary Organic Aerosol SOF Soluble Organic Fraction Characterization of PM of Traffic Origin in Singapore 2004 viii Nomenclature TEF Toxic Equivalency Factor TPE Tampines Expressway TSP Total Suspended Particle UFP Ultrafine Particle VOCs Volatile Organic Compounds Symbols Cc Cunningham slip correction d50 Particle diameter with 50% cut point da Aerodynamic diameter dm Mobility diameter Dp Particle diameter DP50 Particle diameter with 50% removal efficiency ki(x) Kernel function n number of stages s MOUDITM manufacture-specified steepness xmax Upper size limit xmin Lower size limit xp Particle diameter σ Standard deviation Σ Summation λ Mean free path of air ρ0 Unit density ρe Effective particle density Characterization of PM of Traffic Origin in Singapore 2004 ix List of Figures List of Figures Figure 2.1 Saharan dust flows over the Mediterranean Sea towards Italy on July 16, 2003 captured by NASA/Seawifs Satellite. (Source: ESPERE http://www.espere.net/)..............................................................7 Figure 2.2 Volcano St. Helen erupted on May 18, 1980, injecting tons of ash and acidic gases into the atmosphere. (Photo courtesy: The Many Faces of Mt. St. Helens. http://www.olywa.net/radu/valerie/StHelens.html Available: [accessed 25 June 2004]. ...............................................................................................8 Figure 2.3 Traffic emission is the major source of particulate matter in urban environment while industrial emission is another main contributor to atmospheric particulate matter in developed countries. (Photo source: http://www.freefoto.com) .............................................................9 Figure 2.4 Route of formation of SOA. (Source: Seinfeld and Pankow, 2003) .........12 Figure 2.5 Typical diesel engine exhaust particle size distribution in number, mass and surface area weightings (Kittelson, 1998; Kittelson et al., 2002b). ...................................................................................................21 Figure 2.6 Typical composition and structure of engine exhaust particles (Kittelson, 1998).....................................................................................23 Figure 2.7 Typical particle composition for a heavy-duty diesel engine (Kittelson, 1998).....................................................................................24 Figure 2.8 Fate of particles by normal clearance pathway (left) and those enter the interstitial compartment of the lung (right) (Donaldson et al., 1998). .....................................................................................................27 Characterization of PM of Traffic Origin in Singapore 2004 x List of Figures Figure 2.9 Effect of particles on cloud droplet formation and properties (Source: ESPERE, 2004). .......................................................................30 Figure 3.1 Field sampling locality map in this study (Note: AYE, BKE, CTE, ECP, KJE, PIE, SLE and TPE are expressways). ....................................32 Figure 3.2 Boon Lay bus interchange layout plan (provided by Land Transport Authority of Singapore). .........................................................35 Figure 5.1 Average PM2.5 mass concentration measured at Boon Lay bus interchange, Punggol and NUS. ..............................................................51 Figure 5.2 Typical PM mass size distribution obtained from NUS FoE Air Quality Monitoring Station, Punggol multi-storey car park rooftop and Boon Lay bus interchange. ...............................................................57 Figure 5.3 Black carbon (absorbing IR-880nm wavelength) mass concentration diurnal emission profile comparison at NUS, Boon Lay bus interchange and Punggol............................................................59 Figure 5.4 Total particle number concentration emission profile by ELPI at Boon Lay bus interchange (measured from 1st to 3rd Nov 03) and NUS FoE Air Quality Monitoring Station (measured from 7th to 8th Dec 03)...................................................................................................64 Figure 5.5 Particle number concentration and black carbon mass concentration 24-hour emission profile at Boon Lay bus interchange. ............................................................................................66 Figure 5.6 72 hours number concentration size distribution at the Boon Lay bus interchange measured by ELPI between 1st and 4th Nov 03 ...............67 Characterization of PM of Traffic Origin in Singapore 2004 xi List of Figures Figure 5.7 24 hours number concentration size distribution at the NUS FoE air quality monitoring station measured by ELPI from 6th to 7th Dec 03. ...................................................................................................67 Figure 5.8 Number size distribution at the Boon Lay bus interchange measured on 7 Jan 04 from 12:00 to 14:45 with 15 minutes sampling interval. ...................................................................................68 Figure 5.9 Number size distribution at NUS FoE air quality monitoring station measured on 10 Jan 04 from 11:30 to 14:30 with 15 minutes up-scan time. .............................................................................69 Figure 5.10 Correlation between total PAHs and Benzo(g,h,i)perylene. .....................88 Figure 5.11 Correlation between total PAH and Benzo(a)pyrene. ..............................89 Figure 5.12 Major chemical components of PM2.5 sampled at the NUS FoE air quality monitoring station, Punggol multi-storey car park rooftop and Boon Lay bus interchange. ...............................................................92 Figure 5.13 Concentration of SO2 and NOx (NO & NO2) at the each sampling sites measured by Annular Denuder System (ADS). ...............................94 Figure 5.14 Comparison of sulphate mass concentration size distribution at Boon Lay bus interchange and NUS FoE air quality monitoring station.....................................................................................................95 Figure 5.15 Comparison of nitrate mass concentration size distribution at Boon Lay bus interchange and NUS FoE air quality monitoring station. ..........98 Figure 5.16 Comparison of chloride mass concentration size distribution at Boon Lay bus interchange and NUS FoE air quality monitoring station.....................................................................................................98 Characterization of PM of Traffic Origin in Singapore 2004 xii List of Figures Figure 5.17 Comparison of sodium mass concentration size distribution at Boon Lay bus interchange and NUS FoE air quality monitoring station..................................................................................................99 Figure 5.18 Comparison of ammonium mass concentration size distribution at Boon Lay bus interchange and NUS FoE air quality monitoring station................................................................................................101 Figure 5.19 Size distribution of Al, Cu, Fe, Mn, Pb, Zn, Ti and V at Boon Lay bus interchange..................................................................................102 Figure 5.20 Size distribution of Al, Cu, Fe, Mn, Pb, Zn, Ti and V at NUS FoE air quality monitoring station. ............................................................103 Figure A.1 48-hours Weatherlink® meteorology data from 11 to 12 December 2003 recorded at NUS FoE Air Quality Monitoring Station. ..............110 Figure A.2 48-hours Weatherlink® meteorology data from 9 to 10 January 2004 recorded at NUS FoE Air Quality Monitoring Station. ..............110 Characterization of PM of Traffic Origin in Singapore 2004 xiii List of Tables List of Tables Table 2-1 Summary of main reaction mechanism of secondary aerosols formation. ...............................................................................................11 Table 2-2 Particle number and surface area comparison of different sizes of spherical particles. ..................................................................................15 Table 4-1 ADS coating solution preparation, absorbing species identification, denuder coating and extraction procedures..............................................38 Table 4-2 Specification of aerosol number measuring capable instruments. ............43 Table 4-3 Ion Chromatography Analysis Species....................................................46 Table 4-4 Metrohm Ion Chromatography System Operating Parameters.................46 Table 5-1 Spatial variability of PM2.5 mass loading in Boon Lay bus interchange. ..52 Table 5-2 Mass median aerodynamic diameter of each mode reported elsewhere....56 Table 5-3 Real times average BC mass concentration measured by AethalometerTM at NUS, Punggol and Boon Lay bus interchange. ..........58 Table 5-4 Particle number concentration at three sampling sites, measured by CPC (24hours)........................................................................................63 Table 5-5 Comparison of ultrafine particles number concentration (0.008 - 0.074 µm) to total particle number concentration (0.008 - 10 µm) at the University and the bus interchange measured by ELPI............................65 Table 5-6 Average concentration of ions in PM2.5 collected by using MiniVol® at Punggol, NUS and Boon Lay bus interchange.........................................72 Table 5-7 Mean concentration of trace elements in PM2.5 collected by using MiniVol® at Punggol, NUS and Boon Lay bus interchange.....................79 Characterization of PM of Traffic Origin in Singapore 2004 xiv List of Tables Table 5-8 n-Alkanes identified and quantified in 24 hours TSP samples collected at Boon Lay bus interchange by Hi-Volume air sampler HVP3800AFC/230. ........................................................................................84 Table 5-9 PAHs and nitro-PAHs mass concentration in 24 hours TSP samples collected at Boon Lay bus interchange by Hi-Volume air sampler HVP-3800AFC/230. ...............................................................................87 Table 5-10 B(a)P equivalent concentrations of individual PAHs concentrations: risk assessment for PAHs exposure at NUS and Boon Lay bus interchange. ............................................................................................90 Characterization of PM of Traffic Origin in Singapore 2004 xv Chapter 1 Introduction Chapter 1 Introduction Airborne particulate matter (PM) is a highly complex entity representing a mixture of primary emissions and secondary species formed in the atmosphere, and acts as a carrier of non-airborne toxic and carcinogenic materials such as PAHs due to its large surface area (Morawska and Thomas, 2000). In recent years, PM in urban cities has been under much scientific scrutiny because of its potential acute and chronic adverse health effects. An extensive epidemiological study carried out by Schwartz (1994) revealed that 578 more cases of deaths (25% of the deaths were due to chronic lung disease) occurred during high particulate air pollution days (TSP average mass concentration of 141 µg/m3) in Philadelphia than normal. Based on this study, it was hypothesized that increased airborne PM exposure might elevate mortality and morbidity. A number of toxicological studies have concluded that ultrafine particles (UFPs) are more toxic than larger particles with similar mass and chemical composition due to their efficient deposition in the pulmonary interstitial spaces (Ferin et al., 1992; Oberdörster, 1996, 2001; Donaldson et al., 1998, 2001), possibly triggering respiratory and cardiovascular complications (Schwartz, 1994; Samet et al., 2000). Recent animal studies demonstrated that UFPs could be translocated to interstitial sites in the respiratory tract and the liver (Oberdörster et al., 2002) via blood circulation (Nemmar et al., 2002). Recent studies by Oberdörster et al. (2004) revealed that UFPs deposited on the olfactory mucosa of the rat could be translocated to the olfactory bulb of the brain via the olfactory nerve. This means that inhaled UFPs may trigger a similar reaction in these organs like in cardio-pulmonary system. Characterization of PM of Traffic Origin in Singapore 2004 1 Chapter 1 Introduction In view of the adverse health implications associated with tiny airborne particles particularly UFPs, many studies have investigated the various possible sources of particles in the atmosphere so that effective air pollution control measures can be taken to mitigate their emission. Traffic emission, particularly of diesel origin, is a major source of airborne particles in urban air (Shi et al., 1999; Hitchins et al., 2000; Colvile et al., 2001; Zhu et al., 2002; Ashmore, 2001). Airborne particles derived from vehicular sources contain not only organic compounds, but also substantial amounts of ionic species, heavy metals, and trace elements (Park et al., 2003; Sakurai et al., 2003; Shi et al., 1999; USEPA, 2002). As a result of rapid urbanization and transportation demand, diesel engines are widely used in transportation, power generation, and other industrial applications (Lloyd and Cackette, 2001), contributing to high concentration of airborne particles in many urban cities (Nanzetta and Holmén, 2004; Weijers et al., 2004; Vignati et al., 1999) including Singapore. The phenomenal economic growth in Singapore has led to rising automobile ownership and use, resulting in traffic congestion and air pollution issues (Chin, 1996). To address these problems, the government authority in Singapore had implemented vehicle quota scheme to control vehicles growth, and improved the infrastructure of public transport system by consolidating the public bus services and initiating the construction of the Mass Rapid Transit (MRT) system in 1982. Bus interchanges were built as a transit point to serve more than 2 million commuters daily (SBS Transit, 2004a) from the local bus routes to the well-established MRT network. Since the public buses are diesel-powered, the bus interchanges are potential pollution hot spots in Singapore due to emissions of particles and gaseous pollutants from idling buses. Characterization of PM of Traffic Origin in Singapore 2004 2 Chapter 1 Introduction Exposure of commuters and occupants of nearby buildings and residential houses to these diesel emissions is of considerable concern. Exposure dosage plays an important role in determining the influence of PM on human health, which is related to the concentration of pollutants in exhaust fumes and the duration of an individual’s actual exposure (Weijers et al., 2004; Ghio and Huang, 2004). Controlled emission studies were carried out by several research groups using chassis dynamometers to investigate the physical and chemical characteristic of particles emitted from diesel engines (Tanaka and Shimizu, 1999; Gonzalez Gomez et al., 2000; Miyamoto et al., 1997). However the results obtained from the controlled laboratory investigations may not reflect the actual particle concentration, size distribution and chemical composition of particles emitted from on-road vehicles. Stationary air quality monitoring stations have been established to routinely monitor urban air quality. However, the data obtained only reveal the daily average concentrations at fixed monitoring sites, and do not sufficiently represent pollution “hot-spots”, which are characterized by higher-than-average pollution levels. Therefore, a range of emission and exposure studies have been conducted at specific hot-spots such as at road sides, street canyons, tunnels and highways (Unal et al., 2004; Abu-Allaban et al., 2004; Gouriou et al., 2004; Zhu et al., 2002; Molnár et al., 2002; Wehner et al., 2002; Wåhlin et al., 2001). Although these emission studies provided valuable information on the physical and chemical characteristics of particles derived from on-road vehicles, the exposure level of commuters in a confined bus interchange and that of the general public in urban microenvironments still remain poorly understood. Characterization of PM of Traffic Origin in Singapore 2004 3 Chapter 1 Introduction It is critically important to study the levels and characteristics of freshly emitted diesel particulate matter at the busy bus interchanges in Singapore in order to evaluate the risk associated with the exposure of commuters and sensitive members of the general population to UFPs. Since no such data are currently available in the published literature for countries with a high population density like Singapore, an extensive field study was undertaken in Singapore to fill the important knowledge gaps pertaining to diesel emissions and their impact on human health. 1.1 Objectives This project was carried out to investigate and compare the air quality at a major pollution hot spot in Singapore (Boon Lay bus interchange) with that of an urban background location with the following specific objectives: 1) To investigate the physical characteristics of airborne PM at a major bus interchange; 2) To quantify the chemical contents of airborne PM of various sizes at the same location; 3) To assess the risk of toxicity exposure of individuals in the bus interchange. Characterization of PM of Traffic Origin in Singapore 2004 4 Chapter 2 Literature Review Chapter 2 Literature Review 2.1 Sources of Atmospheric Particulate Matter The category of air pollutants called "respirable particulate matter" includes liquids, hydrocarbons, soot, dusts and smoke particles that are smaller than 10 microns in diameter (USEPA, 1997). Invisible to our naked eyes, these respirable particles appear in various sizes and shapes with very complex make up. This makes them inherently more difficult to analyse and study than gas-phase aerosols in the atmosphere (Harrison and Grieken, 1998). Atmospheric particulate matter normally exists in very small size, which makes the particles airborne and capable of travelling over long distance due to their lightweight. The 1997 regional haze episode caused by the forest fires in Indonesia was an evidence of long-range transport of particulate matter derived from biomass burning which had contributed to trans-boundary air pollution in Singapore and other countries in the region (Koe et al., 2001). Particulate matter comes from natural and anthropogenic sources. They can be directly emitted as primary aerosol, or they can be formed from chemical reaction in the atmosphere. Carbonaceous particles are the most commonly known primary aerosols emitted from motor vehicle. Sulphur dioxide (SO2), an acidic gas, released from motor vehicles is oxidized in humid air to form sulphuric acid aerosols, which indirectly become one of the major constituents in the formation of secondary particles in the atmosphere. Such secondary aerosols will be further discussed in section 2.1.2. Characterization of PM of Traffic Origin in Singapore 2004 5 Chapter 2 Literature Review 2.1.1 Natural sources Particles are generally either emitted directly into the atmosphere or produced in the atmosphere from the physical and chemical transformation of other vapour or gaseous pollutants. Marine agitation, volcanic eruption, forest fires ignited by lightning, winds and soil erosion (producing fugitive dust) and photochemical reactions (complex chain reactions between sunlight and gaseous pollutants) are some of the natural sources of particulate matter in the ambient air. Marine Aerosol Aerosols emitted from the sea are known as sea salt aerosols. They are formed from sea spray coming from waves at high wind speeds and by the bursting of entrained air bubbles during whitecap formation. These processes produce coarse mode aerosol of larger than 10 µm in diameter. Such aerosols are commonly enriched in sodium chloride, potassium chloride, calcium sulphate and sodium sulphate. Mineral Aerosol Wind is one of the natural forces that are responsible for the formation of mineral aerosol by picking up the particles from land surface, especially when the soil is dry and desiccated. These mineral aerosols may contain materials derived from the Earth’s crust which usually are rich in iron, aluminium oxides and calcium carbonate. Deserts are the main origin of mineral aerosols. Satellite picture as shown in Figure 2.1 illustrates that the Saharan dust was transported by wind over the Mediterranean Sea heading towards Italy. Characterization of PM of Traffic Origin in Singapore 2004 6 Chapter 2 Literature Review Figure 2.1 Saharan dust flows over the Mediterranean Sea towards Italy on July 16, 2003 captured by NASA/Seawifs Satellite. (Source: ESPERE http://www.espere.net/) Volcanic Aerosol Volcanic eruption is one of the most dynamic natural forces that inject huge amounts of gases and aerosols into the atmosphere. The eruption is so strong that it infuses tons of acidic gases and particles high into the stratosphere. The acidic gases tend to be oxidized and condensed to form fine secondary aerosols. The primary and secondary aerosols can remain in the upper atmosphere for a long period of time before settling to the ground. It is believed that stratospheric particles have a significant impact on climate change and global warming (ESPERE, 2004). Characterization of PM of Traffic Origin in Singapore 2004 7 Chapter 2 Literature Review Figure 2.2 Volcano St. Helen erupted on May 18, 1980, injecting tons of ash and acidic gases into the atmosphere. (Photo courtesy: The Many Faces of Mt. St. Helens. Available: http://www.olywa.net/radu/valerie/StHelens.html [accessed 25 June 2004]. Biogenic Aerosol Some particles can be produced from living organisms or plants. These particles are called biogenic aerosols. Some examples include primary aerosols such as pollens, fungi spores, bacteria and viruses. Biomass burning due to land clearance and burning of agricultural waste is also regarded as one of the sources of biogenic aerosol. 2.1.2 Anthropogenic sources Primary carbonaceous PM The major anthropogenic source of atmospheric particles is through fossil-fuel combustion (which produces ash and soot) in industrial processes (involving refinery, metals smelting, incineration) and transportation (exhaust emission, particles from wear on road, tyres and brakes, resuspension from road surface), which emits PM directly into the atmosphere. Internal combustion engine exhaust emission is regarded as one of Characterization of PM of Traffic Origin in Singapore 2004 8 Chapter 2 Literature Review the main contributors of ambient PM in the urban environment. Field investigations in the Netherlands revealed that concentrations of number and mass of PM increase along with the degree of urbanization due to contribution of vehicular emissions (Weijers et al., 2004). In the United Kingdom, emission inventories of sources revealed that most of the particulates in urban air arise from road traffic (APEG, 1999). Air pollution associated with transport sector has been partly responsible for acid rain formation and also climate change (Colvile et al., 2001). Nevertheless, traffic emitted PM is of concern due to its close proximity to human beings and its potential adverse impacts on human health and urban air quality. Other than traffic and industrial emissions, particles are also produced at home through activities including residential wood fire and indoor cooking activities (Lee et al., 2001; Morawska et al., 2003; Wallace et al., 2004). Figure 2.3 Traffic emission is the major source of particulate matter in urban environment while industrial emission is another main contributor to atmospheric particulate matter in developed countries. (Photo source: http://www.freefoto.com) In urban atmosphere, airborne particles are mostly derived from automobiles emissions (APEG, 1999). Motor vehicles emit not only primary particles, but also reactive gases such as NO, SO2, NH3, and hydrocarbon vapours that react chemically in the atmosphere to form secondary aerosol mass (Allen et al., 2000). Characterization of PM of Traffic Origin in Singapore 2004 9 Chapter 2 Literature Review Secondary aerosols from in situ nucleation Gaseous pollutants such as SO2 and NOx may condense on pre-existing particulate matter to form bigger and denser aerosols. These gases, alternatively, may go through a gas-to-particle homogeneous nucleation forming new particles in the atmosphere. Both natural and human activities in combination release significant amount of secondary aerosols precursors into the atmosphere continuously, periodically or intermittently. Combustion of fossil fuels in power plants and in vehicles is considered to be the two major contributors to the formation of secondary particles with the abundant emission of SO2, NOx and VOCs. The oxidation of SO2 and NOx are the main atmospheric reactions that produce significant amounts of secondary aerosols in the atmosphere. It is estimated that about 50% of the acidic gases are oxidized prior to deposition (Denterner and Crutzen, 1998). Sulphate particle formation is the bestknown example. As shown in Table 2-1, SO2 reacts with OH radicals forming H2SO4 vapour, which will either condense on pre-existing particles or homogeneously nucleate to form sulphate particles. Under the favourable conditions of high H2SO4 production rate, high relative humidity, low temperature and low pre-existing PM concentration, nucleated particles can be formed in huge numbers within a short period of time (Seinfeld, 2004). However, these particles are mostly found in nanometre size range. Hence, their mass is generally negligible compared to the rest of the particle mass distribution. However, their number is dominating the total number concentration of particles in the atmosphere. These nanoparticles may coagulate via collision and adherence to form larger particles. Characterization of PM of Traffic Origin in Singapore 2004 10 Chapter 2 Table 2-1 Literature Review Summary of main reaction mechanism of secondary aerosols formation. Aerosol Species Precursors/Reactants Source Reactions Sulphate Aerosol ¤ SO2 ¤ Automobile 1) O3 + uv O2+O· ¤ Dimethyl Sulphide ¤Volcanic activities 2) H2O+O· H·+OH· ¤ H2S ¤ Marine phytoplankton 3) SO2+OH· HSO3 ¤ OH· (radical) ¤ Power plant 4) HSO3+O2 SO3+HO2 ¤ O3 ¤ Vegetation & animal 5) SO3+H2O H2SO4 decay 6) H2SO4+2NH3 ¤ NO2 ¤ Automobile 1) NO2+OH· ¤ NH3 ¤ Fertilizer or ¤ OH· (radical) ¤ Power plant 2) NO2+O3 Nitrate Aerosol HNO3 NO3+O2 3) NO3+NO2 ¤ O3 NH4SO4 4) N2O5+H2O 5) HNO3+NaCl N2O5 2HNO3 NaNO3+HCl or 6) HNO3+NH3 Organic Aerosol NH4NO3 ¤ VOCs i.e. Toluene ¤ Automobile Most of the VOCs go through ¤ NOx ¤ Refinery photo-oxidation with O3, OH or ¤ O3 NOx reaction. Reference: Seinfeld, 2004; Seinfeld and Pankow, 2003; ten Brink, 2003. Secondary organic aerosol (SOA) is formed when higher polarity and lower volatility oxidation products of certain VOCs condense on pre-existing aerosols (Seinfeld and Pankow, 2003). However, only organic molecules of six or more carbon atoms are capable of producing oxidized products, which condense to form SOA. This is because high carbon atom number organic compounds will produce oxidized products of low vapour pressure. Figure 2.4 illustrates the route of formation of secondary organic PM. Characterization of PM of Traffic Origin in Singapore 2004 11 Chapter 2 Literature Review The low volatility or “semi-volatile” products will either condense on pre-existing particles or nucleate homogeneously to form new mass of particles. Gas Phase Oxidation VOCs Oxidation Products uv, NOx, O3 Products remain in gas phase (High Vapour Pressure) “Semi-Volatile” Products Gas – Particle Partitioning Atmospheric Evolution Inorganic Organic Water Nucleation SOA Primary particles Figure 2.4 Route of formation of SOA. (Source: Seinfeld and Pankow, 2003) 2.2 Measurement of Particulate Matter In this study, only atmospheric PM concentration measurements are discussed. Measurement of PM from direct vehicular exhaust emission involving a dilution tunnel has a different approach of measuring the PM mass, number, surface and size distribution. 2.2.1 Particle mass Particle mass is determined by collecting airborne particles simply by drawing atmospheric air through a filter element of specific porosity with the assumption that all particles that are smaller than the filter pore size would be trapped. The filter is weighed before and after particle collection. The weighed mass is then divided by the Characterization of PM of Traffic Origin in Singapore 2004 12 Chapter 2 Literature Review total volume of air that passed through the filter, which yields mass concentration of particles in a known volume of air. Particle mass concentration of various restricted size range, such as PM10, PM2.5 or PM1.0, is measured by replacing size selective inlets, which only allow selected particle size to reach the filter. Size selectivity is achieved by impaction or inertial collection using a cyclone at a designated airflow rate. Particle mass concentration is measured by two common methodologies: 1) tapered element oscillating microbalance (TEOM) sampler and 2) gravimetric sampler. TEOM measures the particle mass by collecting the particles on a small filter located on a tip of a tapered glass element, which forms part of an oscillation microbalance. The oscillation frequency of the microbalance will change with the mass of particles collected on the filter. In TEOM sampling, inlet air stream is pre-heated to about 50oC, inadvertently removing all of semi-volatile particles, which may represent a significant portion of particle mass in certain area (Harrison et al., 2000). On the other hand, gravimetric sampler i.e. MiniVol® collects the particle mass without any pre-heating involved. Hence, the aerosol samples collected gravimetrically may reveal more hidden information about the sampling field air quality and aerosol apportionment. Currently, the mass of particles smaller than 100 nm in diameter is measured by means of collecting particles in size-fractionated cascade impactors. However, no instrument with an inlet of 100 nm selectivity has been designed to specifically determine the ultrafine particle mass. Characterization of PM of Traffic Origin in Singapore 2004 13 Chapter 2 Literature Review 2.2.2 Particle number The number of particles in a specific volume of air can be measured by the use of condensation nucleus counters (CNCs) or condensation particulate counters (CPC). Continuous CNCs draw particles through a zone saturated with alcohol vapour, mainly n-butanol or isopronanol, which is cooled subsequently to condense the vapour on the particles (Stolzenburg and McMurry, 1991). The condensation will cause the particle to grow to the order of 10 µm in diameter. These particles then become very effective in light scattering, which are then monitored through counting the signals from particles by passing through a light beam or a photometric mode that determines 90o scattered intensity of incident light. The cut size of the CNCs is dependent on the design and degree of supersaturation achieved. Most of the particle counters have a lower cut size of about 3 nm to 20 nm in less sophisticated devices. The upper size limit is determined by the inlet aspiration efficiency, which is likely to be around 5 µm. 2.2.3 Particle surface area When particles decrease in size, for an equal mass of particles, the surface area exposed increases. Traffic emitted particles are always less than 1 µm in diameter by both number and mass measuring methodology. As a result, PM10 and PM2.5 are neither suitable nor effective to measure the impact of vehicle emissions. In a strongly trafficinfluenced urban environment, PM1 makes up only a few percent by mass measurement, but would provide in excess of 95% of the surface area and number concentration. As shown in Table 2-2, assuming spherical particles of equal mass, PM0.01 has a surface area of 1000 times larger than that of PM10. Therefore, it is reasonable that health impacts are best correlated to surface area - the area available to carry toxins into the lungs (Morawska and Thomas, 2000). There are limited methods and devices to Characterization of PM of Traffic Origin in Singapore 2004 14 Chapter 2 Literature Review measure surface area. Hence, it is rarely measured from any direct device except one called an epiphaniometer which determine the Fuchs surface area of particles (Gaggeler et al., 1989), by attaching a gaseous radionuclide to the particle surface and counting collected radioactivity. Nevertheless, surface area can be estimated by measuring the particle size distribution with known or assumed particle geometry. Table 2-2 Particle number and surface area comparison of different sizes of spherical particles. PARTICLE size PM10 PM2.5 PM1.0 PM0.1 PM0.01 Number for equal mass 1 64 1000 1000,000 1,000,000,000 Surface area for equal mass 1 4 10 100 1000 Functional classification Coarse mode Accumulation mode Nuclei mode Source: Morawska and Thomas (2000). 2.2.4 Particle size classification Airborne particles are generated in different sizes, shapes, density and composition from different sources. Generally, it is widely accepted that in atmospheric studies, ambient PM is divided into the following categories based on their aerodynamic diameter: PM10 - particulates of an aerodynamic diameter of less than 10 µm PM2.5 - fine particles of diameters below 2.5 µm Ultrafine particles of diameters below 0.1 µm or 100 nm Nanoparticles, characterized by diameters of less than 50 nm. Aerodynamic diameter is the diameter of a 1 g/cm3 density sphere of the same settling velocity in air as the measured particle. Due to the association of the fine particles and adverse health effect, the United States Environmental Protection Agency (USEPA) has Characterization of PM of Traffic Origin in Singapore 2004 15 Chapter 2 Literature Review imposed strict air quality standards (National Ambient Air Quality Standards-NAAQS) to regulate ambient level of PM10 and PM2.5 of not exceeding 50 µg/m3 and 15 µg/m3 in terms of annual average concentration, respectively (USEPA, 1997). However, air quality standard is yet to be imposed on ambient level of ultrafine particle ( smooth distribution' write(*,*)' Input files : user-specified datafile; free format' write(*,*)' Output files : user-specified; must be *.CSV' write(*,*) write(*,*)' Input file format : ' write(*,*)' line 1 : sample name, max 20 characters' write(*,*)' line 2 : number of ionic species (I3)' PRINT*, " line 3 : species names, space delimited, max 15 chrs" PRINT*, " lines 4-15 : 12 lines, space-delimited, species data" PRINT*, " ### note that all 12 stages must have valid data ###" write(*,*) c nstages = 13 ! number of real+ ficticious MOUDI stages do i=1, nstages numstage(i) = i-2 ! give stages correct MOUDI numbers enddo decades = 3.6 ! number of decades in particle radius > 0.01 æm dbin = 0.05 ! width of size bins wanted, log radius units ndiam = int(decades/dbin) do i = 1,ndiam d(i) = 1.0*10.0**(-2.0 + dbin*(i-1)) dlog(i) = alog10(d(i)) enddo c call kernel c call readdata c do i=1, nspecies c c c set up initial guess distribution totalion = 0.0 do j = 1, nstages totalion = totalion + data(j,i) enddo iddata = i c call initdist c call integ1 Characterization of PM of Traffic Origin in Singapore 2004 112 Appendix C 1000 2000 3000 4000 scalefac = totalion/sumout do j = 1,ndiam fguess(j) = fguess(j)*scalefac enddo call iterate enddo write(6,1000)(save2(k,1),k=1,iddata) write(6,2000)(save2(k,2),k=1,iddata) write(6,3000)(save2(k,3),k=1,iddata) write(6,4000)(save2(k,4),k=1,iddata) format('obs. total',',',80(f9.3,',')) format('inv. total',',',80(f9.3,',')) format('# of itrns',',',80(f7.3,',')) format('%rmsresidl',',',80(f7.3,',')) do k=1,ndiam write(6,5000) d(k),(save1(l,k),l=1,nspecies) c c If RADIUS is to be written out, must divide d(k) here by 2! c If you change this here you must also change it at line 190 c 5000 format(80(1pe12.5,',')) enddo close(6) end ccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccc c c subroutine readdata c reads in MOUDI data c ccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccc subroutine readdata character fnamein*12, fnameout*12, sampname*20, specname*15 common/one/ ndiam, nstages, d(500), dlog(500), fkern(13,500), & numstage(13), dbin, fguess(500), sumout, totalion common/three/ nspecies, specname(80), data(80,80), iddata write(*,*)' Type in input filename : ' read(*,*)fnamein open(5, file = fnamein) write(*,*)' Type in output filename : ' read(*,*)fnameout open(6, file = fnameout, status = 'new') open(5, file = fnamein) read(5,1000) sampname 1000 format(a12) read(5,2000) nspecies 2000 format(i2) do j=1,1 read(5,*)(specname(i), i=1, nspecies) enddo do i=1,nstages-1 read(5,*)(data(13-i,j), j=1,nspecies) enddo do j = 1,nspecies data(13,j) = data(12,j)*0.10 enddo close(5) write(6,1000) sampname write(6,3000)'species',(specname(i), i=1,nspecies) 3000 format(80(a15,',')) return end ccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccc c c subroutine kernel - calculates stage kernel functions for c MOUDI impactor. Uses function functn. c ccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccc subroutine kernel common/one/ ndiam, nstages, d(500), dlog(500), fkern(13,500), & numstage(13), dbin, fguess(500), sumout, totalion common/five/ fkernmax(13) dimension t(15, 500) do i = 1,nstages do j = 1,ndiam t(i,j) = 1 - functn(i,d(j)) enddo enddo c do j = 1, ndiam fkern(1,j) = functn(1,d(j))*(1.0-functn(0,d(j))) Characterization of PM of Traffic Origin in Singapore 2004 113 Appendix C & & & & & & & fkern(2,j) = functn(2,d(j))*t(1,j) fkern(3,j) = functn(3,d(j))*t(1,j)*t(2,j) fkern(4,j) = functn(4,d(j))*t(1,j)*t(2,j)*t(3,j) fkern(5,j) = functn(5,d(j))*t(1,j)*t(2,j)*t(3,j)*t(4,j) fkern(6,j) = functn(6,d(j))*t(1,j)*t(2,j)*t(3,j)*t(4,j)*t(5,j) fkern(7,j) = functn(7,d(j))*t(1,j)*t(2,j)*t(3,j)*t(4,j)*t(5,j) *t(6,j) fkern(8,j) = functn(8,d(j))*t(1,j)*t(2,j)*t(3,j)*t(4,j)*t(5,j) *t(4,j)*t(7,j) fkern(9,j) = functn(9,d(j))*t(1,j)*t(2,j)*t(3,j)*t(4,j)*t(5,j) *t(6,j)*t(7,j)*t(8,j) fkern(10,j) = functn(10,d(j))*t(1,j)*t(2,j)*t(3,j)*t(4,j)*t(5,j) *t(6,j)*t(7,j)*t(8,j)*t(9,j) fkern(11,j) = functn(11,d(j))*t(1,j)*t(2,j)*t(3,j)*t(4,j)*t(5,j) *t(6,j)*t(7,j)*t(8,j)*t(9,j)*t(10,j) fkern(12,j) = functn(12,d(j))*t(1,j)*t(2,j)*t(3,j)*t(4,j)*t(5,j) *t(6,j)*t(7,j)*t(8,j)*t(9,j)*t(10,j)*t(11,j) fkern(13,j) = functn(13,d(j))*t(1,j)*t(2,j)*t(3,j)*t(4,j)*t(5,j) *t(6,j)*t(7,j)*t(8,j)*t(9,j)*t(10,j)*t(11,j)*t(12,j) enddo c do i=1,nstages thing=0.0 do j=1, ndiam thing=amax1(thing,fkern(i,j)) enddo fkernmax(i)=thing enddo cccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccc c c next section is only used if kernel functions are to be written out c cccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccc c c c c c c c c open (5, file = 'imptest.dat', status = 'new') do i = 1, nstages do j = 1, ndiam write(5,*) i, d(j), fkern(i,j) write(*,*) i, d(j), fkern(i,j) enddo enddo close(5) ccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccc return end ccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccc c c function function - calculates MOUDI stage collection functions c according to the Winklmayr et al. anaytical function c c stage cut-points are given for particle density of 2.0 g/cm3 c c stage 1 is ficticious c c stage 13 is the final filter; it has a ficticious lower cut-off c ccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccc function functn(nstage,d) common/two/ d50(13), s(13) d50(1) = 100.0000 d50(2) = 18.0000 d50(3) = 10.0000 d50(4) = 5.6000 d50(5) = 3.2000 d50(6) = 1.8000 d50(7) = 1.0000 d50(8) = 0.5200 d50(9) = 0.2950 d50(10) = 0.1660 d50(11) = 0.0940 d50(12) = 0.0530 d50(13) = 0.0200 s(1) = 10.0000 s(2) = 9.8128 s(3) = 20.7851 s(4) = 7.4232 s(5) = 5.6099 s(6) = 10.2459 s(7) = 11.5074 Characterization of PM of Traffic Origin in Singapore 2004 114 Appendix C s(8) = 5.5326 s(9) = 4.7948 s(10) = 4.2440 s(11) = 3.9850 s(12) = 2.5821 s(13) = 2.0000 if(nstage.ne.0)then functn = 1/(1 + (d50(nstage)/d)**(2.0*s(nstage))) else functn = 1/(1 + (2.0*d50(1)/d)**(2.0*s(1))) endif return end cccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccc c c subroutine initdist c produces an initial guess distribution from the raw MOUDI data c cccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccc subroutine initdist character specname*15 common/one/ ndiam, nstages, d(500), dlog(500), fkern(13,500), & numstage(13), dbin, fguess(500), sumout, totalion common/two/ d50(13), s(13) common/three/ nspecies, specname(80), data(80,80), iddata c a1=0.0 do i=1,nstages if(data(i,iddata).gt.a1)then a1=data(i,iddata) a3=d50(i) endif enddo a2=2.0 do j=1,ndiam fguess(j) = funcdist(d(j),a1,a2,a3) enddo return end ccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccc c c subroutine integ1 c determines integral of fguess over all diameter values c ccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccc subroutine integ1 common/one/ ndiam, nstages, d(500), dlog(500), fkern(13,500), & numstage(13), dbin, fguess(500), sumout, totalion sum = 0.0 do i=1,ndiam sum = sum + fguess(i) enddo sumout = sum*dbin return end ccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccc c c subroutine iterate c carries out iterative inversion c cccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccc subroutine iterate character specname*15 common/one/ ndiam, nstages, d(500), dlog(500), fkern(13,500), & numstage(13), dbin, fguess(500), sumout, totalion common/three/ nspecies, specname(80), data(80,80), iddata common/four/idstage, amount, ratio common/six/save1(80,500),save2(80,4) c nrep = 10 ! number of iterations sumer=0.0 rms=0.0 rmsold=1.e3 do iter=1,nrep if(rms.gt.0.)rmsold=rms sumer=0.0 c ermax=0.0 do j=2,nstages idstage=j Characterization of PM of Traffic Origin in Singapore 2004 115 Appendix C c c & & call integ ratio=data(j,iddata)/amount sumer=sumer+(ratio-1.0)**2 ermax=amax1(ermax,abs(ratio-1.0)) sumer=sumer+(data(j,iddata)-amount)**2 call alter thing=0.0 do i=1,ndiam thing=amax1(thing,fguess(i)) enddo do i=1,ndiam fguess(i)=amax1(thing*1.e-2,fguess(i)) enddo do i=3,ndiam-3 fguess(i) = (fguess(i-2)*0.1111+fguess(i-1)*0.3333 + fguess(i) + fguess(i+1)*0.1111+fguess(i+2)*0.3333)/1.888 c c the original smoothing weights used by Jill were 0.25,0.5,1,0.5,0.25 c enddo fguess(2)=(0.333*fguess(1)+fguess(2)+0.333*fguess(3))/1.667 fguess(ndiam-2)=fguess(ndiam-3)& (fguess(ndiam-4)-fguess(ndiam-3)) this=fguess(ndiam-2)/fguess(ndiam-3) fguess(ndiam-1)=fguess(ndiam-2)& this*(fguess(ndiam-3)-fguess(ndiam-2)) this=fguess(ndiam-1)/fguess(ndiam-2) fguess(ndiam)=fguess(ndiam-1)& this*(fguess(ndiam-2)-fguess(ndiam-1)) call integ1 totalmas=sumout do ij= 1,ndiam fguess(ij)=fguess(ij)*totalion/sumout enddo enddo rms=sqrt(sumer/nstages) rms=100.*rms/totalion if(abs(rms-rmsold)/rmsold.lt.0.001.or.iter.eq.nrep)then do i=1,ndiam save1(iddata,i)=fguess(i) enddo save2(iddata,1)=totalion save2(iddata,2)=totalmas save2(iddata,3)=real(iter) save2(iddata,4)=rms return endif enddo return end cccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccc c c subroutine integ c cccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccc subroutine integ character specname*15 common/one/ ndiam, nstages, d(500), dlog(500), fkern(13,500), & numstage(13), dbin, fguess(500), sumout, totalion common/three/ nspecies, specname(80), data(80,80), iddata common/four/idstage, amount, ratio sum=0. do i=1,ndiam sum=sum+fguess(i)*fkern(idstage,i) enddo amount=sum*dbin return end ccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccc c c subroutine alter c ccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccc subroutine alter common/one/ ndiam, nstages, d(500), dlog(500), fkern(13,500), & numstage(13), dbin, fguess(500), sumout, totalion common/four/idstage, amount, ratio common/five/ fkernmax(13) Characterization of PM of Traffic Origin in Singapore 2004 116 Appendix C do i=1,ndiam if(fkern(idstage,i).gt.0.0001)then fguess(i)=fguess(i)*(1.0+(ratio-1.0) & *(fkern(idstage,i)/fkernmax(idstage))**1.0) endif enddo return end CCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC C C C FUNCTION funcdist(XI,A) C C C C Purpose : The function is for the log-normal distribution C C specified as C C C C __ __ C C dN A(1).ln(10) | -sqr[ln{r/A(3)}] | C C ---- = ------------------- * exp| -------------------- | C C dlog r sqrt[2*PI] * A(2) | 2 * sqr[ A(2) ] | C C --- C CCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC FUNCTION funcdist(XI,a1,a2,a3) C PI=3.141592654 TWO_PI = SQRT(2.0 * PI) DLOG_1 = ALOG(XI/A3) ** 2 VALUE_1 = -DLOG_1 / (2.0 * (A2 ** 2)) IF (VALUE_1 .LT. -700.0) VALUE_1 = -700.0 C func = A1 /( TWO_PI * A2 ) * EXP(VALUE_1) funcdist = func if(funcdist.lt.1.e-5)funcdist=1.e-5 RETURN END Characterization of PM of Traffic Origin in Singapore 2004 117 References References Abu-Allaban, M., Rogers, C. 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(1997), Size-resolved Airborne Particles and Their Morphology in Central Jakarta, Atmospheric Environment, Vol. 31 (8), pp. 1167-1172. - End - Characterization of PM of Traffic Origin in Singapore 2004 140 [...]... chemical contents of airborne PM of various sizes at the same location; 3) To assess the risk of toxicity exposure of individuals in the bus interchange Characterization of PM of Traffic Origin in Singapore 2004 4 Chapter 2 Literature Review Chapter 2 Literature Review 2.1 Sources of Atmospheric Particulate Matter The category of air pollutants called "respirable particulate matter" includes liquids,... soot) in industrial processes (involving refinery, metals smelting, incineration) and transportation (exhaust emission, particles from wear on road, tyres and brakes, resuspension from road surface), which emits PM directly into the atmosphere Internal combustion engine exhaust emission is regarded as one of Characterization of PM of Traffic Origin in Singapore 2004 8 Chapter 2 Literature Review the main... University and the bus interchange measured by ELPI 65 Table 5-6 Average concentration of ions in PM2.5 collected by using MiniVol® at Punggol, NUS and Boon Lay bus interchange .72 Table 5-7 Mean concentration of trace elements in PM2.5 collected by using MiniVol® at Punggol, NUS and Boon Lay bus interchange 79 Characterization of PM of Traffic Origin in Singapore 2004 xiv List of Tables Table 5-8... well-established MRT network Since the public buses are diesel-powered, the bus interchanges are potential pollution hot spots in Singapore due to emissions of particles and gaseous pollutants from idling buses Characterization of PM of Traffic Origin in Singapore 2004 2 Chapter 1 Introduction Exposure of commuters and occupants of nearby buildings and residential houses to these diesel emissions is of considerable... mass of particles smaller than 100 nm in diameter is measured by means of collecting particles in size-fractionated cascade impactors However, no instrument with an inlet of 100 nm selectivity has been designed to specifically determine the ultrafine particle mass Characterization of PM of Traffic Origin in Singapore 2004 13 Chapter 2 Literature Review 2.2.2 Particle number The number of particles in. .. 2002; Wåhlin et al., 2001) Although these emission studies provided valuable information on the physical and chemical characteristics of particles derived from on-road vehicles, the exposure level of commuters in a confined bus interchange and that of the general public in urban microenvironments still remain poorly understood Characterization of PM of Traffic Origin in Singapore 2004 3 Chapter 1 Introduction... Characterization of PM of Traffic Origin in Singapore 2004 1 Chapter 1 Introduction In view of the adverse health implications associated with tiny airborne particles particularly UFPs, many studies have investigated the various possible sources of particles in the atmosphere so that effective air pollution control measures can be taken to mitigate their emission Traffic emission, particularly of diesel origin, ... exposure at NUS and Boon Lay bus interchange 90 Characterization of PM of Traffic Origin in Singapore 2004 xv Chapter 1 Introduction Chapter 1 Introduction Airborne particulate matter (PM) is a highly complex entity representing a mixture of primary emissions and secondary species formed in the atmosphere, and acts as a carrier of non-airborne toxic and carcinogenic materials such as PAHs... materials derived from the Earth’s crust which usually are rich in iron, aluminium oxides and calcium carbonate Deserts are the main origin of mineral aerosols Satellite picture as shown in Figure 2.1 illustrates that the Saharan dust was transported by wind over the Mediterranean Sea heading towards Italy Characterization of PM of Traffic Origin in Singapore 2004 6 Chapter 2 Literature Review Figure 2.1 Saharan... engines are widely used in transportation, power generation, and other industrial applications (Lloyd and Cackette, 2001), contributing to high concentration of airborne particles in many urban cities (Nanzetta and Holmén, 2004; Weijers et al., 2004; Vignati et al., 1999) including Singapore The phenomenal economic growth in Singapore has led to rising automobile ownership and use, resulting in traffic .. .CHARACTERISATION OF PARTICULATE MATTER OF TRAFFIC ORIGIN IN SINGAPORE YANG TZUO SERN (B Eng (Hons), RMIT) A THESIS SUBMITTED FOR THE DEGREE OF MASTER OF ENGINEERING DEPARTMENT OF CHEMICAL... commuters in a confined bus interchange and that of the general public in urban microenvironments still remain poorly understood Characterization of PM of Traffic Origin in Singapore 2004 Chapter Introduction... contents of airborne PM of various sizes at the same location; 3) To assess the risk of toxicity exposure of individuals in the bus interchange Characterization of PM of Traffic Origin in Singapore